Computational investigation of NO adsorption and dissociation on the silicon-embedded graphene catalyst: A density functional theory perspective.

One of the encouraging processes to protect the environment is the catalytic conversion of NO and other harmful greenhouse gases. Employing heteroatom dopants into the Graphene structure for this conversion is an attractive technique owing to its relatively low price and the very low destructive impacts. DFT was applied to explore fundamental and principal reactions of NO adsorption and dissociation over the Silicon-embedded Graphene catalyst to contribute to the search for green catalysts in the conversion of toxic gases into less harmful ones. Forming a surface peroxy group O, NO bond cleavage and oxygen atom transfer were theoretically investigated. It is found that the NO molecule requires +0.52, +0.88 and + 0.4 eV of activation energies through mentioned three reactions, respectively, to adsorb and decompose to N and O. The parallel, lying-atop-011 and flat were stable forms with adsorption energies of -0.20 (-4.65), -0.19 (-4.53) and -0.18 (-4.46) and -0.19 eV (-4.53 kcal/mol), respectively. The achieved outcomes reveal that Silicon-embedded Graphene has a high potential to be used as a more efficient and green catalyst for the catalytic conversion of the air polluting gases in comparison to the Selenium-doped Graphene, Fe, Manganese-embedded Graphene and Magnesium oxide (MgO) catalysts.